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    Development of ultra-sensitive and selective molecularly imprinted polymer-based electrochemical sensor for L-lactate detection
    (Elsevier, 2024) Piskin, Ensar; Cetinkaya, Ahmet; Eryaman, Zulal; Karadurmus, Leyla; Unal, Mehmet Altay; Sezgintürk, Mustafa Kemal; Hizal, Julide
    Lactate detection is important for the food and healthcare industries, and it's especially important when there's tissue hypoxia, hepatic illness, bleeding, respiratory failure, or sepsis. A new molecularly imprinted polymer (MIP) based electrochemical sensor was fabricated for differential pulse voltammetric assay of L-lactate (LAC). By using ZIF-8@ZnQ nanoparticles, the number of regions and effective surface area were increased. The polymeric film was obtained using 4 aminobenzoic acid (4-ABA) as a functional monomer, ethylene glycol dimethacrylate (EGDMA) as a cross-linker, 2-hydroxyethyl methacrylate (HEMA) as basic monomers, and 2-hydroxy-2-methylpropiophenone one as initiator. The developed 4-ABA/LAC/ZIF-8@ZnQ@MIP-GCE was morphologically characterised using SEM and electrochemically using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) measurements. A linear range of 0.1-1.0 pM LAC with a detection limit of 29.9 fM was found. Lastly, the MIP-based electrochemical sensor detected LAC in commercial human serum samples.
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    Öğe
    The Evaluation of Clinical Applications for the Detection of the Alzheimer's Disease Biomarker GFAP
    (Taylor & Francis Inc, 2024) Ozcelikay-Akyildiz, Goksu; Karadurmus, Leyla; Cetinkaya, Ahmet; Uludag, Inci; Ozcan, Burcu; Unal, Mehmet Altay; Sezgintürk, Mustafa Kemal
    One of the most prevalent neurodegenerative diseases is Alzheimer's disease (AD). The hallmarks of AD include the accumulation of amyloid plaques and neurofibrillary tangles, which cause related secondary diseases, progressive neurodegeneration, and ultimately death. The most prevalent cell type in the human central nervous system, astrocytes, are crucial for controlling neuronal function. Glial fibrillary acidic protein (GFAP) is released from tissue into the bloodstream due to astrocyte breakdown in neurological diseases. Increased levels of GFAP in the serum can function as blood markers and be an effective prognostic indicator to help diagnose neurological conditions early on, from stroke to neurodegenerative diseases. The human central nervous system (CNS) is greatly affected by diseases associated with blood GFAP levels. These include multiple sclerosis, intracerebral hemorrhage, glioblastoma multiforme, traumatic brain injuries, and neuromyelitis optica. GFAP demonstrates a strong diagnostic capacity for projecting outcomes following an injury. Furthermore, the increased ability to identify GFAP protein fragments helps facilitate treatment, as it allows continuous screening of CNS injuries and early identification of potential recurrences. GFAP has recently gained attention due to data showing that the plasma biomarker is effective in identifying AD pathology. AD accounts for 60-70% of the approximately 50 million people with dementia worldwide. It is critical to develop molecular markers for AD, whose number is expected to increase to about 3 times and affect humans by 2050, and to investigate possible targets to confirm their effectiveness in the early diagnosis of AD. In addition, most diagnostic methods currently used are image-based and do not detect early disease, i.e. before symptoms appear; thus, treatment options and outcomes are limited. Therefore, recently developed methods such as point-of-care (POC), on-site applications, and enzyme-linked immunosorbent assay-polymerase chain reaction (ELISA-PCR) that provide both faster and more accurate results are gaining importance. This systematic review summarizes published studies with different approaches such as immunosensor, lateral flow, POC, ELISA-PCR, and molecularly imprinted polymer using GFAP, a potential blood biomarker to detect neurological disorders. Here, we also provide an overview of current approaches, analysis methods, and different future detection strategies for GFAP, the most popular biosensing field.